The teachings herein are directed to a method and apparatus for resizing a halftone image using halftone tile parameters.
Demands imposed by today's digital media handling in regards to document edit-ability, portability, and dynamic layout make simple solutions for image resizing obsolete. Consider that a document can be rasterized and halftoned for a particular print path. That document may be directed to a different printer, possibly years later when extracted from an archive, with different paper size capabilities and may require image editing, cropping and resizing of halftoned image content prior to printing on the given print engine. Halftoned images may generally be re-purposed to print on different paper sizes and require layout modifications and resizing. Printed halftone images may be scanned in a setting such as at a digital copier, and a user may wish to modify the image attributes such as size, aspect ratio, or image content. Conventional resizing methods that utilize spatially consistent interpolation methods are unsuitable in this halftone image setting because interpolation methods introduce defects in halftone image structure and such spatially consistent interpolation can distort image content.
To begin, consider the halftone image class of concern to the present teachings herein. With the advent of inexpensive digital color printers, methods and systems of color digital halftoning have become increasingly important in the reproduction of printed or displayed images possessing continuous color tones. It is well understood that most digital color printers operate in a binary mode, i.e., for each color separation, a corresponding color spot is either printed or not printed at a specified location or pixel. Digital halftoning controls the printing of color spots, where the spatial averaging of the printed color spots by either a human visual system or a viewing instrument, provides the illusion of the required continuous color tones.
The most common halftone technique is screening, which compares the required continuous color tone level of each pixel for each color separation with one or more predetermined threshold levels. The predetermined threshold levels are typically defined for a rectangular cell that is tiled to fill the plane of an image, thereby forming a halftone screen of threshold values. At a given pixel, if the required color tone level is darker than the given halftone threshold level, a color spot is printed at that specified pixel. Otherwise the color spot is not printed. The output of the screening process is a binary pattern of multiple small “dots,” which are regularly spaced as is determined by the size, shape, and tiling of the halftone cell. In other words, the screening output, as a two-dimensionally repeated pattern, possesses two fundamental spatial frequencies, which are completely defined by the geometry of the halftone screen.
It is understood in the art that the distribution of printed pixels depends on the design of the halftone screen. For clustered-dot halftone screens, all printed pixels formed using a single halftone cell typically group into one or more clusters. If a halftone cell only generates a single cluster, it is referred to as a single-dot halftone or single-dot halftone screen. Alternatively, halftone screens may be dual-dot, tri-dot, quad-dot, or the like.
While halftoning is often described in terms of halftone dots, it should be appreciated that idealized halftone dots can possess a variety of shapes that include rectangles, squares, lines, circles, ellipses, “plus signs,” X-shapes, pinwheels, and pincushions, and actual printed dots can possess distortions and fragmentation of those idealized shapes introduced by digitization and the physical printing process. Various digital halftone screens having different shapes and angles are described in U.S. Pat. No. 4,149,194, “Variable Angle Electronic Halftone Screening” to inventor Thomas M. Holladay, which is hereby incorporated by reference in its entirety.
A current practice for resizing an image is to perform some type of resampling interpolation of the input image to generate an output image with the desired number of samples in each dimension. But, resampling a halftone image with an interpolator such as nearest-neighbor, linear, quadratic, or cubic can result in defects within the halftone image. One particularly problematic defect is the introduction of gray levels that must be re-halftoned prior to printing, where the re-halftoning step creates an interference pattern with the input halftone image structure. Another defect is the appearance of seams along columns or rows of pixels, where the resampled halftone samples have a local disturbance in phase with respect to the halftone frequency. Yet another defect associated with these resampling methods is that the aspect ratio of important image content can become distorted. For example, use of resampling to reduce the vertical dimension of an image can make people appear shorter and wider than they are in reality.
Another practice for resizing a halftone image is simply to crop that image to the desired size. However, cropping can delete desired image content around the borders of the halftone image.
The diversity and versatility of display devices today imposes new demands on digital media. For instance, designers must create different alternatives for web-content and design different layouts for different display and rendering devices. These demands have lead to development of increasingly sophisticated image resizing tools for continuous tone digital images. Avidan and Shamir, in “Seam Carving for Content-Aware Image Resizing” ACM Transactions on Graphics, Volume 26, Number 3, SIGGRAPH 2007, present a simple image operator called seam carving, that supports content-aware image resizing for both image reduction and image expansion. A seam is an optimal eight-connected path of pixels on a single image from top to bottom, or left to right, where optimality is defined by a low value of an image energy function. By repeatedly carving out or inserting seams in one direction, Avidan and Shamir can change the aspect ratio of an image. By applying these operators in both directions they can retarget the image to a new size. The selection and order of seams protect the content of the image, as defined by the energy function. Seam carving can also be used for image content enhancement and object removal. The seam carving method of Avidan and Shamir can support various visual saliency measures for defining the energy of an image, and can also include user input to guide the process. By storing the order of seams in an image they create multi-size images that are able to continuously change in real time to fit a given size.
The method of Avidan and Shamir cannot be readily applied to halftone images because selecting low energy seams will result in visually undesirable pathological seams that travel between halftone dots or along chains of connected dots. Removing a low-energy seam that travels between halftone dots would only increase the local darkness in the region about the seam. Conversely, removing a low-energy seam that traveled along connected halftone dots will decrease local darkness in the region about the seam. In either case, the seams would appear as visible streaks and would quite likely be objectionable. For example an input halftone image where the pixels are at 600 dpi (dots per inch) resolution, and the halftone is at 141 cpi (cells per inch) at 450 when resized by 10% in the horizontal direction by applying a low energy seam removal method directly on the halftone image caused undesirable streaks to appear in the image.
One further option for resizing a halftone image is to apply a descreening technique to the halftone image to remove the halftone dot structure and provide a continuous tone version of the image. The continuous tone version of the image could be resized using the method of Avidan and Shamir. After resizing, the image may be rehalftoned to finally produce a resized binary image. However, a key problem with that approach is that any such descreening technique tends to blur fine details within an image and the resulting image will have an excessively “soft” appearance. This softness problem will be particularly evident when applied in binary printer image paths and copier image paths that utilize a “copy dot” approach to reproduction. “Copy dot” refers to direct copying of a halftone image without descreening and rescreening. Resizing such a descreened image will induce a blurring that “copy dot” reproduction is intended to avoid.
As provided herein, there are supplied teachings to systems and methods for resizing a halftone image using halftone tile parameters. One approach entails receiving into a digital imaging system, a digital halftone image and a desired resizing factor for the digital halftone image. Subsequently the system will define cells within the digital halftone image and determine from those cells, a number of halftone tile seams to suitable for manipulation. The orientation of these halftone tile seams is dictated by the received desired resizing factor. The seam energy of the number of halftone tile seams is determined according to an energy metric so as to provide indication of at least one low energy determined halftone tile seam. A resizing of the halftone image is then performing by iteratively deleting at least one low energy halftone tile seam in the halftone image. The resized halftone image may then be printed on a printer.
Also disclosed in embodiments herein is an image forming method for resizing a digital halftone image. The approach entails receiving into a digital imaging system, a digital halftone image and a desired resizing factor for that digital halftone image. The system will then define cells within the digital halftone image and determine from those cells, a number of halftone tile seams to suitable for manipulation. The orientation of these halftone tile seams is dictated by the received desired resizing factor. The seam energy of these halftone tile seams is then determined according to an energy metric so as to provide indication of a number of low energy determined halftone tile seams. The number of low energy seams identified is sufficient to achieve the desired resizing factor. A resizing of the halftone image is then performing by iteratively deleting the low energy determined halftone tile seams within the halftone image. The resized halftone image may then be printed on a printer.
Further disclosed in embodiments herein is an image forming method for resizing a digital halftone image. The method entails receiving into a digital imaging system, a digital halftone image and a desired resizing factor for that digital halftone image. The system will then define cells within the digital halftone image and determine from those cells, a number of halftone tile seams to suitable for manipulation. The orientation of these halftone tile seams is dictated by the received desired resizing factor. The digital halftone image is descreened to provide an energy map. The seam energy of these halftone tile seams is then determined according to the energy map so as to provide indication of a number of low energy determined halftone tile seams. The number of low energy seams identified is at least sufficient to achieve the desired resizing factor for the digital halftone image. A resizing of the halftone image is then performing by iteratively deleting the number of low energy determined halftone tile seams within the halftone image to obtain a resized image. The resized halftone image may then be printed on a printer.